ArticleRadiological physics and technology2026
Comparative evaluation of feature-based and intensity-based algorithms for dosimetric registration in radiotherapy quality assurance using electronic portal imaging devices.
Article in Radiological physics and technology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
To evaluate image registration as a quantitative alternative to the gamma index for VMAT patient-specific quality assurance and to benchmark feature-based against intensity-based registration algorithms. We retrospectively analyzed 93 EPID-verified VMAT arcs using five registration algorithms: three feature-based (SIFT, Thin-Plate Splines, CONCORD) and two intensity-based (B-spline, Demons). We assessed the ability of each algorithm to align absolute dose distributions on a common coordinate grid. Dosimetric agreement was quantified using a dual-parameter metric combining linear regression slope (tolerance 95–105%) and the coefficient of determination [Formula: see text] Standard gamma analysis (3%/3 mm, 90% passing rate) served as the clinical reference. Agreement with gamma-based classification was evaluated using Cohen’s kappa [Formula: see text]. Feature-based methods significantly outperformed intensity-based models. The dose-specific CONCORD algorithm achieved the highest initial agreement with gamma analysis [Formula: see text]. Application of the dual-parameter metric further enhanced diagnostic specificity; specifically, CONCORD’s agreement improved to [Formula: see text] with 95.7% accuracy. In contrast, intensity-based deformable models exhibited poor performance and high false-negative rates. This behavior introduces non-physical dose warping that obscures clinically relevant delivery errors. Registration-based dose comparison offers a robust, quantitative alternative to the gamma index. By utilizing a global affine transformation and dose-specific topological features, the CONCORD algorithm effectively detects localized and systematic discrepancies without the error-masking risks inherent in generic deformable registration. This framework aligns with AAPM TG-307 objectives, offering a more granular and physically intuitive assessment of VMAT delivery fidelity.
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